In software maintenance work, software architects and programmers need to identify modules that require modification or deletion. Whilst user requests and bug reports are utilised for this purpose, evaluating the execution status of modules within the software is also crucial. This paper, therefore, applies spatial statistics to assess internal software execution data. First, we define a software space dataset, viewing the software's internal structure as a space based on module call relationships. Then, using spatial statistics, we conduct the visualization of spatial clusters and the statistical testing using spatial measures. Finally, we consider the usefulness of spatial statistics in the software engineering domain and future challenges. (This paper has been accepted for publication in the Proceedings of MODELSWARD 2026)

翻译：在软件维护工作中，软件架构师和程序员需要识别需要修改或删除的模块。尽管用户请求和错误报告常被用于此目的，评估软件内部模块的执行状态同样至关重要。因此，本文应用空间统计方法来评估内部软件执行数据。首先，我们定义了一个软件空间数据集，将软件内部结构视为基于模块调用关系的空间。随后，利用空间统计方法，我们进行了空间聚类的可视化以及基于空间度量的统计检验。最后，我们探讨了空间统计在软件工程领域的应用价值及未来挑战。（本文已被MODELSWARD 2026会议论文集录用）